A subjective methodology for risk quantification based on generalized fuzzy numbers

Abstract

Uncertain information and domain experts' knowledge are inevitable in risk analysis of complex systems. Fuzzy reasoning is one of the ways to handle uncertainty. In addition, in order to represent the confidence degree of experts' subjective assessment, generalized fuzzy numbers are used for risk quantification in this paper. Based on the generalized fuzzy numbers arithmetic operation, a simple algorithm is developed to obtain final risk, which is also represented as generalized fuzzy number. A new similarity measure is proposed to determine the risk level. Compared with the previous works, our method is more reasonable. A numerical example is used to show the efficiency of the proposed method.

Keywords:

• Risk analysis
• Generalized fuzzy numbers
• Subjective assessment
• Natural language

Acknowledgements

Many thanks for the anonymous reviewers' careful reading and constructive comments for improving the paper. The work is partially supported by National High Technology Project (863), Grant No. 2006AA02Z320, National Natural Science Foundation of China, Grant No. 30700154, Zhejiang Province Nature Sciences Foundation, Grant No. Y107458, National Defence Key Laboratory, Grant No. 51476040105JW0301, 51476040103JW13, Aerospace Basic Support Foundaton, Grant No. 2004-JD-4, School Youth Fund of Shanghai Jiao Tong University.